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Prediction of deformations of steel plate by artificial neural network in forming process with induction heating
Truong-Thinh Nguyen
The Journal of Mechanical Science and Technology, vol. 23, no. 4, pp.1211-1221, 2009
Abstract : To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction
process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation
of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the
difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In
this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical
method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux
itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses
on the plate to obtain deformations during the heating process are then performed with a commercial FEM program
for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship
between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a
wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network
is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs.
The predicted outputs from the neural network are compared with those of the experiments and the numerical
results. They are in good agreement.
Keyword : Plate forming; Electro-magnetic induction; Thermo-mechanical analysis; Deformation; FEM; Artificial neural network |
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